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Symmetry: Modeling the Effects of Masking Noise, Axial Cueing and Salience
Symmetry detection is an interesting probe of pattern processing because it requires the matching of novel patterns without the benefit of prior recognition. However, there is evidence that prior knowledge of the axis location plays an important role in symmetry detection. We investigated how the pr...
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Formato: | Texto |
Lenguaje: | English |
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Public Library of Science
2010
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2850314/ https://www.ncbi.nlm.nih.gov/pubmed/20386600 http://dx.doi.org/10.1371/journal.pone.0009840 |
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author | Chen, Chien-Chung Tyler, Christopher W. |
author_facet | Chen, Chien-Chung Tyler, Christopher W. |
author_sort | Chen, Chien-Chung |
collection | PubMed |
description | Symmetry detection is an interesting probe of pattern processing because it requires the matching of novel patterns without the benefit of prior recognition. However, there is evidence that prior knowledge of the axis location plays an important role in symmetry detection. We investigated how the prior information about the symmetry axis affects symmetry detection under noise-masking conditions. The target stimuli were random-dot displays structured to be symmetric about vertical, horizontal, or diagonal axes and viewed through eight apertures (1.2° diameter) evenly distributed around a 6° diameter circle. The information about axis orientation was manipulated by (1) cueing of axis orientation before the trial and (2) varying axis salience by including or excluding the axis region within the noise apertures. The percentage of correct detection of the symmetry was measured at for a range of both target and masking noise densities. The threshold vs. noise density function was flat at low noise density and increased with a slope of 0.75–0.8 beyond a critical density. Axis cueing reduced the target threshold 2–4fold at all noise densities while axis salience had an effect only at high noise density. Our results are inconsistent with an ideal observer or signal-to-noise account of symmetry detection but can be explained by a multiple-channel model is which the response in each channel is the ratio between the nonlinear transform of the responses of sets of early symmetry detectors and the sum of external and intrinsic sources of noise. |
format | Text |
id | pubmed-2850314 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-28503142010-04-12 Symmetry: Modeling the Effects of Masking Noise, Axial Cueing and Salience Chen, Chien-Chung Tyler, Christopher W. PLoS One Research Article Symmetry detection is an interesting probe of pattern processing because it requires the matching of novel patterns without the benefit of prior recognition. However, there is evidence that prior knowledge of the axis location plays an important role in symmetry detection. We investigated how the prior information about the symmetry axis affects symmetry detection under noise-masking conditions. The target stimuli were random-dot displays structured to be symmetric about vertical, horizontal, or diagonal axes and viewed through eight apertures (1.2° diameter) evenly distributed around a 6° diameter circle. The information about axis orientation was manipulated by (1) cueing of axis orientation before the trial and (2) varying axis salience by including or excluding the axis region within the noise apertures. The percentage of correct detection of the symmetry was measured at for a range of both target and masking noise densities. The threshold vs. noise density function was flat at low noise density and increased with a slope of 0.75–0.8 beyond a critical density. Axis cueing reduced the target threshold 2–4fold at all noise densities while axis salience had an effect only at high noise density. Our results are inconsistent with an ideal observer or signal-to-noise account of symmetry detection but can be explained by a multiple-channel model is which the response in each channel is the ratio between the nonlinear transform of the responses of sets of early symmetry detectors and the sum of external and intrinsic sources of noise. Public Library of Science 2010-04-06 /pmc/articles/PMC2850314/ /pubmed/20386600 http://dx.doi.org/10.1371/journal.pone.0009840 Text en Chen, Tyler. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Chen, Chien-Chung Tyler, Christopher W. Symmetry: Modeling the Effects of Masking Noise, Axial Cueing and Salience |
title | Symmetry: Modeling the Effects of Masking Noise, Axial Cueing and Salience |
title_full | Symmetry: Modeling the Effects of Masking Noise, Axial Cueing and Salience |
title_fullStr | Symmetry: Modeling the Effects of Masking Noise, Axial Cueing and Salience |
title_full_unstemmed | Symmetry: Modeling the Effects of Masking Noise, Axial Cueing and Salience |
title_short | Symmetry: Modeling the Effects of Masking Noise, Axial Cueing and Salience |
title_sort | symmetry: modeling the effects of masking noise, axial cueing and salience |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2850314/ https://www.ncbi.nlm.nih.gov/pubmed/20386600 http://dx.doi.org/10.1371/journal.pone.0009840 |
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